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Kilo Code
✓ verifiedFreemium
Open-source AI coding agent for VS Code, JetBrains, CLI and cloud, with 500+ models at zero inference markup and BYOK.
10K visits/mo57K saves
Pricing
No public pricing
No public pricing
No public pricing
Free: $0 (open source; AI usage billed separately)
Teams: $15/user/mo (14-day free trial)
KiloClaw hosting: from $55/mo
Free trial available
No public pricing
Core features
- ✦Automated AWS cost optimization
- ✦Commitment management (Reserved Instances & Savings Plans)
- ✦Cost allocation and chargebacks
- ✦Kubernetes cost management
- ✦Resource rightsizing and scheduling
- ✦Idle resource optimization
- ✦Real-time cost visibility
- ✦Unlimited chatbots deployment
- ✦Automatic retraining on webpages
- ✦Customizable appearance and personality
- ✦One-click deployment to multiple platforms
- ✦User Management
- ✦Custom APIs
- ✦Lifelike voice AI agents
- ✦24/7 availability
- ✦Customer-led conversational platform
- ✦Integration with enterprise systems
- ✦500+ AI models at zero inference markup
- ✦Bring-your-own-keys and local model support
- ✦MIT-licensed, fully open source
- ✦Works in VS Code, JetBrains, CLI and cloud
- ✦Agent modes (Code, Architect)
- ✦Parallel isolated worktrees
- ✦Slack code reviewer and gateway
- ✦Coding education platform for beginners
- ✦Curriculum on Next.js, Vercel, and AI
- ✦AI-powered app development
- ✦Live events and hackathons
- ✦Coding community
- ✦AI-centric platform for software engineers
- ✦Nia AI for code understanding
- ✦Context management and codebase understanding tools
Use cases
- →Reducing AWS costs for startups and enterprises
- →Optimizing EKS and ASG scalability and discounts
- →Maximizing Savings Plans and mitigating commitment risk
- →Automating time-consuming cost optimization tasks
- →Allocating AWS, Kubernetes, GenAI & SaaS costs
- →Customer service chatbots
- →Help desk chatbots
- →HR chatbots
- →Training chatbots
- →Consulting chatbots
- →White labeled chatbot for web apps
- →Answering customer service calls
- →Providing information and support
- →Resolving customer issues
- →Automating call center operations
- →Writing and refactoring production code with AI
- →Planning features before implementation
- →Running agents across multiple IDEs and the CLI
- →Learning to code and build AI-powered applications
- →Developing AI agents that can work with code safely and effectively
- →Empowering developers to orchestrate AI agents across the software lifecycle
- →Improving context management and codebase understanding for AI agents
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